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   &#160;<span id="projectnumber">0.1</span>
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   <div id="projectbrief">Google Summer of Code 2011: Structure from motion</div>
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<div class="title">D:/Travail/These/Determination caracteristiques camera/GSoC/SfM/src/Boost_Matching.cpp</div>  </div>
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<div class="fragment"><pre class="fragment"><a name="l00001"></a>00001 <span class="preprocessor">#include &quot;Boost_Matching.h&quot;</span>
<a name="l00002"></a>00002 
<a name="l00003"></a>00003 <span class="preprocessor">#include &lt;iostream&gt;</span>
<a name="l00004"></a>00004 
<a name="l00005"></a>00005 <span class="keyword">namespace </span>OpencvSfM{
<a name="l00006"></a>00006 
<a name="l00007"></a>00007   <span class="keyword">using</span> cv::Ptr;
<a name="l00008"></a>00008   <span class="keyword">using</span> cv::Mat;
<a name="l00009"></a>00009   <span class="keyword">using</span> std::vector;
<a name="l00010"></a>00010 
<a name="l00011"></a>00011   vector&lt; cv::Ptr&lt; PointsToTrack &gt; &gt;::iterator <a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#af4032a6ff57159ff1854bcb3039c2509" title="End of list images of points. It&#39;s the same for every thread, so set once for every thread before run...">MatchingThread::end_matches_it</a>;
<a name="l00012"></a>00012   vector&lt; cv::Mat &gt; <a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#a78cdb5def6e18e5d8dbbbe5915a9b8fe" title="List of mask to hide some points in the matching computation.">MatchingThread::masks</a>;
<a name="l00013"></a>00013   <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#ada0799eb3adfb43cc720d75b85a35b98" title="Minimum matches between two images to accept the matches.">MatchingThread::mininum_points_matches</a>=50;
<a name="l00014"></a>00014   PointsMatcher* <a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#a560bf2489beba3822c9549f3514c6966" title="The algorithm to use for matching.">MatchingThread::match_algorithm</a> = NULL;
<a name="l00015"></a>00015 
<a name="l00016"></a>00016   DECLARE_MUTEX( MatchingThread::thread_concurr );
<a name="l00017"></a>00017   DECLARE_MUTEX( MatchingThread::thread_unicity );
<a name="l00018"></a>00018 
<a name="l00019"></a>00019 
<a name="l00020"></a><a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#a3509545a5cfbd9994713966116941fcb">00020</a>   <a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#a3509545a5cfbd9994713966116941fcb">MatchingThread::MatchingThread</a>(cv::Ptr&lt;  SequenceAnalyzer&gt; seq_analyser,
<a name="l00021"></a>00021     <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i, std::vector&lt; cv::Ptr&lt; PointsToTrack &gt; &gt;::iterator matches_it)
<a name="l00022"></a>00022   {
<a name="l00023"></a>00023     this-&gt;i = <a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#a584ed4ac0f86b315adb45e3ca91900d1" title="Index of source image. This image will be matched against every other.">i</a>;
<a name="l00024"></a>00024     this-&gt;matches_it = <a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#ace2327ef4f8035da205908bb8ae3cc09" title="iterator of every Points for track (points of other images to match)">matches_it</a>;
<a name="l00025"></a>00025     this-&gt;seq_analyser = <a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#a9f5044ef6e695d5b8e5aeefda5ce7874" title="This object contains every sequence related info (images, points, tracks...)">seq_analyser</a>;
<a name="l00026"></a>00026     this-&gt;seq_analyser.addref();<span class="comment">//avoid ptr deletion...</span>
<a name="l00027"></a>00027   }
<a name="l00028"></a>00028 
<a name="l00029"></a><a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#a63e8b718ecb56468cca7dd66e19de4a4">00029</a>   <span class="keywordtype">void</span> <a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#a63e8b718ecb56468cca7dd66e19de4a4">MatchingThread::operator()</a>()
<a name="l00030"></a>00030   {
<a name="l00031"></a>00031     Ptr&lt;PointsToTrack&gt; points_to_track_i=( *matches_it );
<a name="l00032"></a>00032 
<a name="l00033"></a>00033     points_to_track_i-&gt;computeKeypointsAndDesc( <span class="keyword">false</span> );
<a name="l00034"></a>00034 
<a name="l00035"></a>00035     P_MUTEX( thread_unicity );
<a name="l00036"></a>00036     Ptr&lt;PointsMatcher&gt; point_matcher = <a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#a560bf2489beba3822c9549f3514c6966" title="The algorithm to use for matching.">match_algorithm</a>-&gt;<a class="code" href="class_opencv_sf_m_1_1_points_matcher.html#a30f88f6ce4159fb6539a98768ff071b4">clone</a>( <span class="keyword">true</span> );
<a name="l00037"></a>00037     point_matcher-&gt;add( points_to_track_i );
<a name="l00038"></a>00038     V_MUTEX( thread_unicity );
<a name="l00039"></a>00039     point_matcher-&gt;train( );
<a name="l00040"></a>00040 
<a name="l00041"></a>00041     vector&lt; Ptr&lt; PointsToTrack &gt; &gt;::iterator matches_it1 = <a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#ace2327ef4f8035da205908bb8ae3cc09" title="iterator of every Points for track (points of other images to match)">matches_it</a>+1;
<a name="l00042"></a>00042     <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> j=<a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#a584ed4ac0f86b315adb45e3ca91900d1" title="Index of source image. This image will be matched against every other.">i</a>+1;
<a name="l00043"></a>00043     <span class="keywordflow">while</span> ( matches_it1 != <a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#af4032a6ff57159ff1854bcb3039c2509" title="End of list images of points. It&#39;s the same for every thread, so set once for every thread before run...">end_matches_it</a> )
<a name="l00044"></a>00044     {
<a name="l00045"></a>00045       Ptr&lt;PointsToTrack&gt; points_to_track_j=( *matches_it1 );
<a name="l00046"></a>00046 
<a name="l00047"></a>00047       points_to_track_j-&gt;computeKeypointsAndDesc( <span class="keyword">false</span> );
<a name="l00048"></a>00048 
<a name="l00049"></a>00049       P_MUTEX( thread_unicity );
<a name="l00050"></a>00050       Ptr&lt;PointsMatcher&gt; point_matcher1 = <a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#a560bf2489beba3822c9549f3514c6966" title="The algorithm to use for matching.">match_algorithm</a>-&gt;<a class="code" href="class_opencv_sf_m_1_1_points_matcher.html#a30f88f6ce4159fb6539a98768ff071b4">clone</a>( <span class="keyword">true</span> );
<a name="l00051"></a>00051       point_matcher1-&gt;add( points_to_track_j );
<a name="l00052"></a>00052       V_MUTEX( thread_unicity );
<a name="l00053"></a>00053       point_matcher1-&gt;train( );
<a name="l00054"></a>00054 
<a name="l00055"></a>00055       vector&lt; cv::DMatch &gt; matches_i_j;
<a name="l00056"></a>00056       point_matcher-&gt;crossMatch( point_matcher1, matches_i_j, <a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#a78cdb5def6e18e5d8dbbbe5915a9b8fe" title="List of mask to hide some points in the matching computation.">masks</a> );
<a name="l00057"></a>00057 
<a name="l00058"></a>00058       <span class="comment">//First compute points matches:</span>
<a name="l00059"></a>00059       <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> size_match=matches_i_j.size( );
<a name="l00060"></a>00060       vector&lt;cv::Point2f&gt; srcP;
<a name="l00061"></a>00061       vector&lt;cv::Point2f&gt; destP;
<a name="l00062"></a>00062       vector&lt;uchar&gt; status;
<a name="l00063"></a>00063 
<a name="l00064"></a>00064       <span class="comment">//vector&lt;KeyPoint&gt; points1 = point_matcher-&gt;;</span>
<a name="l00065"></a>00065       <span class="keywordflow">for</span>( <span class="keywordtype">size_t</span> cpt = 0; cpt &lt; size_match; ++cpt ){
<a name="l00066"></a>00066         <span class="keyword">const</span> cv::KeyPoint &amp;key1 = point_matcher1-&gt;getKeypoint(
<a name="l00067"></a>00067           matches_i_j[ cpt ].queryIdx );
<a name="l00068"></a>00068         <span class="keyword">const</span> cv::KeyPoint &amp;key2 = point_matcher-&gt;getKeypoint(
<a name="l00069"></a>00069           matches_i_j[ cpt ].trainIdx );
<a name="l00070"></a>00070         srcP.push_back( cv::Point2f( key1.pt.x,key1.pt.y ) );
<a name="l00071"></a>00071         destP.push_back( cv::Point2f( key2.pt.x,key2.pt.y ) );
<a name="l00072"></a>00072         status.push_back( 1 );
<a name="l00073"></a>00073       }
<a name="l00074"></a>00074 
<a name="l00075"></a>00075       <span class="comment">//free some memory:</span>
<a name="l00076"></a>00076       point_matcher1-&gt;clear();
<a name="l00077"></a>00077       points_to_track_j-&gt;free_descriptors();
<a name="l00078"></a>00078 
<a name="l00079"></a>00079       Mat fundam = cv::findFundamentalMat( srcP, destP, status, cv::FM_RANSAC, 1 );
<a name="l00080"></a>00080 
<a name="l00081"></a>00081       <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> nbErrors = 0, nb_iter=0;
<a name="l00082"></a>00082       <span class="comment">//refine the mathing :</span>
<a name="l00083"></a>00083       size_match = status.size( );
<a name="l00084"></a>00084       <span class="keywordflow">for</span>( <span class="keywordtype">size_t</span> cpt = 0; cpt &lt; size_match; ++cpt ){
<a name="l00085"></a>00085         <span class="keywordflow">if</span>( status[ cpt ] == 0 )
<a name="l00086"></a>00086         {
<a name="l00087"></a>00087           size_match--;
<a name="l00088"></a>00088           status[ cpt ] = status[ size_match ];
<a name="l00089"></a>00089           status.pop_back( );
<a name="l00090"></a>00090           srcP[ cpt ] = srcP[ size_match ];
<a name="l00091"></a>00091           srcP.pop_back( );
<a name="l00092"></a>00092           destP[ cpt ] = destP[ size_match ];
<a name="l00093"></a>00093           destP.pop_back( );
<a name="l00094"></a>00094           matches_i_j[ cpt ] = matches_i_j[ size_match ];
<a name="l00095"></a>00095           matches_i_j.pop_back( );
<a name="l00096"></a>00096           cpt--;
<a name="l00097"></a>00097           ++nbErrors;
<a name="l00098"></a>00098         }
<a name="l00099"></a>00099       }
<a name="l00100"></a>00100 
<a name="l00101"></a>00101       <span class="keywordflow">while</span>( nbErrors &gt; size_match/10 &amp;&amp; nb_iter &lt; 4 &amp;&amp;
<a name="l00102"></a>00102         matches_i_j.size( ) &gt; <a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#ada0799eb3adfb43cc720d75b85a35b98" title="Minimum matches between two images to accept the matches.">mininum_points_matches</a> )
<a name="l00103"></a>00103       {
<a name="l00104"></a>00104         fundam = cv::findFundamentalMat( srcP, destP, status, cv::FM_RANSAC, 1.5 );
<a name="l00105"></a>00105 
<a name="l00106"></a>00106         <span class="comment">//refine the mathing :</span>
<a name="l00107"></a>00107         nbErrors =0 ;
<a name="l00108"></a>00108         size_match = status.size( );
<a name="l00109"></a>00109         <span class="keywordflow">for</span>( <span class="keywordtype">size_t</span> cpt = 0; cpt &lt; size_match; ++cpt ){
<a name="l00110"></a>00110           <span class="keywordflow">if</span>( status[ cpt ] == 0 )
<a name="l00111"></a>00111           {
<a name="l00112"></a>00112             size_match--;
<a name="l00113"></a>00113             status[ cpt ] = status[ size_match ];
<a name="l00114"></a>00114             status.pop_back( );
<a name="l00115"></a>00115             srcP[ cpt ] = srcP[ size_match ];
<a name="l00116"></a>00116             srcP.pop_back( );
<a name="l00117"></a>00117             destP[ cpt ] = destP[ size_match ];
<a name="l00118"></a>00118             destP.pop_back( );
<a name="l00119"></a>00119             matches_i_j[ cpt ] = matches_i_j[ size_match ];
<a name="l00120"></a>00120             matches_i_j.pop_back( );
<a name="l00121"></a>00121             cpt--;
<a name="l00122"></a>00122             ++nbErrors;
<a name="l00123"></a>00123           }
<a name="l00124"></a>00124         }
<a name="l00125"></a>00125         nb_iter++;
<a name="l00126"></a>00126       };
<a name="l00127"></a>00127 
<a name="l00128"></a>00128       <span class="comment">//refine the mathing:</span>
<a name="l00129"></a>00129       fundam = cv::findFundamentalMat( srcP, destP, status, cv::FM_LMEDS );
<a name="l00130"></a>00130 
<a name="l00131"></a>00131       <span class="comment">//refine the mathing :</span>
<a name="l00132"></a>00132       size_match = status.size( );
<a name="l00133"></a>00133       <span class="keywordflow">for</span>( <span class="keywordtype">size_t</span> cpt = 0; cpt &lt; size_match; ++cpt ){
<a name="l00134"></a>00134         <span class="keywordflow">if</span>( status[ cpt ] == 0 )
<a name="l00135"></a>00135         {
<a name="l00136"></a>00136           size_match--;
<a name="l00137"></a>00137           status[ cpt ] = status[ size_match ];
<a name="l00138"></a>00138           status.pop_back( );
<a name="l00139"></a>00139           srcP[ cpt ] = srcP[ size_match ];
<a name="l00140"></a>00140           srcP.pop_back( );
<a name="l00141"></a>00141           destP[ cpt ] = destP[ size_match ];
<a name="l00142"></a>00142           destP.pop_back( );
<a name="l00143"></a>00143           matches_i_j[ cpt ] = matches_i_j[ size_match ];
<a name="l00144"></a>00144           matches_i_j.pop_back( );
<a name="l00145"></a>00145           cpt--;
<a name="l00146"></a>00146           ++nbErrors;
<a name="l00147"></a>00147         }
<a name="l00148"></a>00148       }
<a name="l00149"></a>00149 
<a name="l00150"></a>00150       <span class="keywordflow">if</span>( matches_i_j.size( ) &gt; <a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#ada0799eb3adfb43cc720d75b85a35b98" title="Minimum matches between two images to accept the matches.">mininum_points_matches</a> &amp;&amp; nb_iter &lt; 4 )
<a name="l00151"></a>00151       {
<a name="l00152"></a>00152         P_MUTEX( thread_unicity );
<a name="l00153"></a>00153         <a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#a9f5044ef6e695d5b8e5aeefda5ce7874" title="This object contains every sequence related info (images, points, tracks...)">seq_analyser</a>-&gt;addMatches( matches_i_j,<a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#a584ed4ac0f86b315adb45e3ca91900d1" title="Index of source image. This image will be matched against every other.">i</a>,j );
<a name="l00154"></a>00154         std::clog&lt;&lt;<span class="stringliteral">&quot;find &quot;</span>&lt;&lt;matches_i_j.size( )&lt;&lt;
<a name="l00155"></a>00155           <span class="stringliteral">&quot; matches between &quot;</span>&lt;&lt;<a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#a584ed4ac0f86b315adb45e3ca91900d1" title="Index of source image. This image will be matched against every other.">i</a>&lt;&lt;<span class="stringliteral">&quot; &quot;</span>&lt;&lt;j&lt;&lt;std::endl;
<a name="l00156"></a>00156         V_MUTEX( thread_unicity );
<a name="l00157"></a>00157       }<span class="keywordflow">else</span>
<a name="l00158"></a>00158       {
<a name="l00159"></a>00159         std::clog&lt;&lt;<span class="stringliteral">&quot;can&#39;t find matches between &quot;</span>&lt;&lt;<a class="code" href="struct_opencv_sf_m_1_1_matching_thread.html#a584ed4ac0f86b315adb45e3ca91900d1" title="Index of source image. This image will be matched against every other.">i</a>&lt;&lt;<span class="stringliteral">&quot; &quot;</span>&lt;&lt;j&lt;&lt;std::endl;
<a name="l00160"></a>00160       }
<a name="l00161"></a>00161       j++;
<a name="l00162"></a>00162       matches_it1++;
<a name="l00163"></a>00163     }
<a name="l00164"></a>00164 
<a name="l00165"></a>00165     P_MUTEX( thread_unicity );
<a name="l00166"></a>00166     point_matcher-&gt;clear();
<a name="l00167"></a>00167     points_to_track_i-&gt;free_descriptors();<span class="comment">//save memory...</span>
<a name="l00168"></a>00168     V_MUTEX( thread_unicity );
<a name="l00169"></a>00169     V_MUTEX( MatchingThread::thread_concurr );<span class="comment">//wake up waiting thread</span>
<a name="l00170"></a>00170   };
<a name="l00171"></a>00171 }
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